Biology subjects

Vogel, E. K.

Publications and source records attributed to Vogel, E. K..

At least 19 recordsLinked to original sources

bioRxiv2026

Degraded neural representations foreshadow failures of sustained attention

Attention prioritizes relevant information from the environment, but does not do so consistently over time. Instead, we sometimes experience poor attentional states which are characterized by a higher degree of performance failures, or "lapses." The source of these lapses--whether they arise from attentional disengagement, failures of attentional selection, or simply failures of response control--is not clear. This study tests whether the strength of neural representations differs as a function of both attentional selection and modulation over time. We recorded electroencephalography (EEG) data while participants performed a sustained attention task requiring the selection of task-relevant items and withholding of responses to rare targets. Results show that relevant items receive prioritized processing in brain signals, as measured with EEG decoding. Yet, their neural representational fidelity weakens under poor sustained attentional states, foreshadowing upcoming behavioral failures. These findings support a neural basis of disengagement during poor attentional states, suggesting that lapses may arise from a decoupling of brain activity from task processing. Finally, pre-item representational strength predicted memory success for targets, suggesting that neural fidelity indexes an encoding-ready state. Results suggest that the quality of neural representations is affected by ongoing attention and plays a key role in processing and memory.

neuroscience↗

bioRxiv2026

Mnemonic Demand Reconfigures the Neural Architecture of Memory Encoding

Memory encoding must accommodate increasingly demanding loads, yet it remains unclear whether the underlying brain state is preserved or adaptively reconfigured as load increases. Here, we recorded EEG from 111 participants performing a visual memory task in which they encoded lists of real images ranging from 1 to 128 items, spanning low to high mnemonic demands, followed by a recognition test. We measured the similarity of set-size-specific interelectrode correlation patterns to a low-load reference. Similarity decreased monotonically as list length increased: patterns at set sizes below 4 remained close to the low-load configuration, whereas set sizes of 8 and above progressively shifted toward a distinct high-load configuration. This transition was captured by a single rotating eigenvector, revealing a low-dimensional trajectory from low- to high-load neural geometry. Smaller rotation angles from the low-load template predicted better memory performance at high loads. Together, these findings provide evidence for adaptive reconfiguration and reveal a structured, low-dimensional neural trajectory through which encoding architecture changes as mnemonic demands increase.

neuroscience↗

bioRxiv2026

Distinct Control States Underlie Voluntary Task Switching: Evidence for Capacity-Dependent Control Modes

People often switch tasks when attention wanes or an alternative task becomes more appealing. Such choices may reflect different control modes that may vary with working memory (WM) capacity. This study tested whether momentary attentional lapses prospectively predict voluntary task switching and whether this relationship depends on WM capacity. Participants performed a continuous performance task involving face and scene images, with blocks in which they either freely chose the next task or followed an externally imposed sequence. The results suggested a capacity-dependent pattern in which individuals with lower WM capacity were more likely to switch following lapse-prone blocks, whereas higher-capacity individuals tended to switch from relatively well-focused states. Eye-tracking revealed greater bias toward the competing irrelevant category before switches in lower-capacity individuals, accompanied by early conflict-related pupil dilation. Externally imposed task sequencing selectively reduced lapses in the lower-capacity group without affecting higher-capacity performance, suggesting that external structure can scaffold weaker internal goal maintenance. These findings suggest that the relationship between lapses and voluntary switching varies with WM capacity rather than being uniform across individuals. This pattern is consistent with a goal-competition account in which lapses reflect shifts in the balance between competing task goals, and voluntary switches may be preceded by different control states.

neuroscience↗

bioRxiv2025

Neural Dynamics Underlying Repeated Learning of Visual Image Sequences

Humans possess a remarkable ability to recognize visual objects with high fidelity, supported by complex neural mechanisms underlying memory retrieval. Event-related potential (ERP) studies have identified two key neural signatures of recognition memory: the parietal old/new effect and the frontal old/new effect. Despite extensive research on these ERP components, the extent to which these components reflect distinct memory processes remains debated. In the present study, we investigated how repetitive learning modulates these ERP components. Participants repeatedly studied a fixed list of 32 real-world images across up to five study-test repetitions while EEG was recorded. Additionally, a separate set size 1 condition served as a proxy for working memory. Our results showed that with increased repetitions, the parietal old/new effect exhibited enhanced amplitude and earlier peak latency, reflecting more efficient retrieval of well-learned memories. In contrast, the frontal old/new effect remained unchanged in both amplitude and timing. These findings suggest that the parietal old/new effect is a sensitive neural marker of learning-related changes in long-term memory representations, while the frontal effect is less influenced by repetition. Additionally, despite similarly high accuracy between the well-practiced set size 32 condition and the set size 1 working memory condition, both parietal and frontal old/new effects peaked significantly earlier for set size 1, suggesting that access to working memory is substantially faster than even well-practiced long-term memory. Together, our results highlight the unique role of the parietal old/new effect, but not the frontal old/new effect, in repetitive learning, despite both components being important for successful recognition of learnt visual stimuli.

neuroscience↗

bioRxiv2025

A unique neural signature of long-term memory encoding from EEG inter-electrode correlation

Classic memory models proposed that the encoding process involved in visual working memory (VWM) controls the bandwidth of encoding in long-term memory (LTM). Behaviorally, VWM and LTM accuracies are reliably correlated at the behavioral level, raising the question of whether LTM encoding uniquely engages processes that are distinct from VWM encoding. To investigate this, we recorded EEG activity as participants completed recognition memory tasks with set sizes of 32 and 128, far beyond typical VWM capacity. Using interelectrode correlation (IC) analysis, we found that IC patterns reliably predicted individual differences in LTM encoding across both set sizes, indicating a robust, domain-general neural signature. Importantly, this predictive power remained even after controlling for VWM and attentional control performance, suggesting that the model captures variance specific to LTM encoding. Temporally, predictive signals emerged only after stimulus onset and persisted for 500-600 ms. Early and late encoding phases involved distinct network structures, reflecting dynamic neural processes underlying individual differences in LTM encoding. Together, our findings reveal a unique and temporally dynamic neural signature that supports individual differences in LTM encoding, independent of general cognitive abilities. Significance StatementHumans maintain visual information using two distinct memory systems: visual working memory, which is capacity-limited, and long-term memory, which has virtually unlimited capacity. Despite their differences, individuals with better VWM performance often show superior LTM performance, raising the question of whether unique LTM encoding abilities exist beyond those accounted for by VWM. Here, we leveraged EEG data to examine interelectrode correlation patterns during memory encoding. Our results show that these neural patterns uniquely predict individual differences in LTM encoding ability, even after controlling for VWM performance. Furthermore, we showed that the interelectrode correlation patterns continuously track the temporal dynamics of LTM encoding over time.

neuroscience↗

bioRxiv2025

Decoding Distraction From the Human Brain: A Unique Neural Signature Beyond Failures of Selective Attention and Control

Attentional lapses are a ubiquitous feature of cognition, yet their underlying causes remain poorly understood. Theories of sustained attention often point to failures of cognitive control in maintaining the task-set, while data-driven approaches suggest that lapses may instead reflect a breakdown in the selection of task-relevant information. This study aimed to characterize the neural mechanisms of sustained attention lapses and to test whether EEG-based signatures of lapse-prone states are distinct from signatures of failures of selective attention and task-set maintenance. Twenty adults completed a sustained attention go/no-go task while focusing on either numbers or letters, with EEG recorded simultaneously. Poor sustained attention was examined at two complementary levels: trial-level lapses, defined as no-go errors, and attentional states, derived from reaction-time variability and categorized as "in-the-zone" versus "out-of-the-zone". Across both levels, suboptimal sustained attention was associated with attenuated event-related potentials, most notably a reduced parietal P3 amplitude and weaker whole-scalp inter-electrode correlation. To isolate a unique EEG marker of lapse-prone state, a machine-learning classifier decoded attentional state from EEG activity. Cross-validated accuracy reached [~]80% and remained robust after controlling for reaction time. Finally, representational similarity analysis confirmed that this neural signature was dissociable from stimulus-side selection and task-set maintenance.

neuroscience↗

bioRxiv2025

Mental Imagery abilities affect visual working memory performance: evidence from aphantasic participants

Visual imagery refers to the mental generation of visual representations of stimuli, while visual working memory involves retaining visual information for a short period without external input. Due to the conceptual overlap between these two constructs, successful performance on visual working memory tasks may rely on the use of visual imagery to rehearse items during the retention interval. Consequently, individuals with aphantasia, who lack voluntary visual imagery, may experience difficulties with such tasks. However, prior research has suggested that some individuals with aphantasia might employ non-visual strategies to compensate for this deficit. In two experiments, we examined visual working memory performance in aphantasic and control participants across a range of stimulus types. In Experiment 1, participants completed a change localization task using color squares and complex fractals; in Experiment 2, stimuli included real words, phonologically valid pseudowords, and phonologically invalid pseudowords. Across both experiments, aphantasic participants demonstrated significantly impaired visual working memory compared to controls. Notably, their performance was equally impaired for stimuli that were easily verbalizable (i.e., colors and words) and those that were not (i.e., fractals and pseudowords). Furthermore, individual differences in visual imagery ability, as measured by the Vividness of Visual Imagery Questionnaire (VVIQ), significantly predicted working memory performance across all stimulus types. These findings provide direct evidence for the critical role of visual imagery in supporting visual working memory.

neuroscience↗

bioRxiv2025

Mechanisms of Output Gating for visual working memory

Working memory (WM) tasks often require comparing remembered items to test displays, but little is known about how people selectively remove irrelevant information at test. Across three experiments, we used contralateral delay activity (CDA) to track WM load and examine selective removal. In Experiment 1, CDA amplitudes increased with set size even when only one item was probed, suggesting minimal removal based on spatial location. Experiment 2 ruled out spatial grouping by presenting items sequentially in the same location, yet more items were retained for larger set size. In Experiment 3, however, when items belonged to distinct mnemonic categories, CDA amplitudes at test were reduced, consistent with selective removal based on category relevance. Additionally, P3 old-new effects showed that decision speed and strength were influenced by the number of items maintained. Together, these results suggest that people selectively remove WM contents based on categorical relevance, not spatial cues, enabling more efficient memory-based decisions.

neuroscience↗

bioRxiv2025

Differential representations of spatial location by aperiodic and alpha oscillatory activity in working memory

Decades of research have shown working memory (WM) relies on sustained pre-frontal cortical activity and visual extrastriate activity, particularly in the alpha (8-12 Hz) frequency range. This alpha activity tracks the spatial location of WM items, even when spatial position is task-irrelevant and there is no stimulus currently being presented. Traditional analyses of putative oscillations using bandpass filters, however, conflate oscillations with non-oscillatory aperiodic activity. Here, we reanalyzed seven different human electroencephalography (EEG) visual WM datasets to test the hypothesis that aperiodic activity-which is thought to reflect the relative contributions of excitatory and inhibitory drive-plays a distinct role in visual WM from true alpha oscillations. To do this, we developed a novel, time-resolved spectral parameterization approach to disentangle oscillations from aperiodic activity during WM encoding and maintenance. Across all seven tasks, totaling 112 participants, we captured the representation of spatial location from total alpha power using an inverted encoding model (IEM), replicating traditional analyses. We then trained separate IEMs to estimate the strength of spatial location representation from aperiodic-adjusted alpha (reflecting just the oscillatory component) and aperiodic activity, and find that IEM performance improves for aperiodic-adjusted alpha compared to total alpha power that blends the two signals. We also discover a novel role for aperiodic activity, where IEM performance trained on aperiodic activity is highest during stimulus presentation, but not during the WM maintenance period. Our results emphasize the importance of controlling for aperiodic activity when studying neural oscillations while uncovering a novel functional role for aperiodic activity in the encoding of visual WM information. Significance statementWorking memory is a crucial component of cognition, yet its neural mechanisms are not fully understood. Research shows that alpha activity - presumed to reflect neural oscillations - tracks the location of items we hold in memory. However, these analyses assume that all alpha power is oscillatory, even though oscillations are mixed with non-oscillatory, aperiodic activity that may be physiologically and functionally distinct. Here, we use a novel analytical approach for separating alpha oscillations and aperiodic activity dynamically across time. Our results reveal distinct roles for each in human visual working memory: aperiodic activity encodes the spatial location of information whereas alpha oscillations maintain the location of that information.

neuroscience↗

bioRxiv2025

Sustained attention is more closely related to long-term memory than to attentional control

Individuals differ in their ability to sustain attention. However, whether differences in sustained attention reflect differences in processes related to attentional control and working memory or long-term memory (LTM) remains underexplored. In Experiment 1, we conducted an online study (n = 136) measuring participants sustained attention, attention control and working memory, and LTM. We measured sustained attention with an audio-visual continuous performance task (avCPT) in which participants responded to images while inhibiting responses to infrequent targets; attention control and working memory with Flanker, change localization, and Simon tasks; and LTM with recognition and source memory tests. Factor analyses revealed that sustained attention formed a distinct factor from attention control and working memory and LTM. Individual differences in the sustained attention factor robustly predicted individual differences in LTM and, to a lesser extent, attention control and working memory. In Experiment 2, to test how neural signatures of sustained attention related to attention control and working memory and LTM, we analyzed fMRI functional connectivity patterns collected as 20 participants performed the avCPT. A pre-trained connectome-based model of sustained attention predicted participants performance on out-of-scanner LTM, but not attention control and working memory, tasks. Together these results suggest that individual differences in sustained attention, although correlated with attention control and working memory, are more closely related to LTM.

neuroscience↗

bioRxiv2024

Objective Markers of Sustained Attention Fluctuate Independently of Mind-Wandering Reports

Sustained attention fluctuates between periods of good and poor attentional performance. Two major methodologies exist to study these fluctuations: an objective approach that identifies "in-the-zone" states of consistent response times (RTs) and "out-of-the-zone" states of erratic RTs and a subjective approach that asks participants whether they are on-task or mind wandering. Although both approaches effectively predict attentional lapses, it remains unclear whether they capture the same or distinct attentional fluctuations. We combined both approaches within a single sustained attention task requiring frequent responses and response inhibition to rare targets to explore their consistency (N=40). Behaviorally, both objective out-of-the-zone and subjective mind-wandering states were associated with more attentional lapses. However, the percentage of time spent out-of-the-zone did not differ between on-task and mind-wandering periods and both objective and subjective states independently predicted error-proneness, suggesting that the two methods do not capture the same type of attention fluctuations. Whereas attentional preparation before correct inhibitions was greater during out-of-the-zone compared to in-the-zone periods, preparation did not differ by subjective state. In contrast, post-error slowing differed by both objective and subjective states, but in opposite directions: slowing was observed when participants were objectively out-of-the-zone or subjectively on-task. Overall, our results provide evidence that objective and subjective approaches capture distinct attention fluctuations during sustained attention tasks. Integrating both objective and subjective measures is crucial for fully understanding the mechanisms underlying our ability to remain focused.

neuroscience↗

bioRxiv2022

Overlapping Neural Representations for Dynamic Visual Imagery and Stationary Storage in Spatial Working Memory

Representations in working memory need to be flexibly transformed to adapt to our dynamic environment and variable task demands. Recent work has demonstrated that activity in the alpha frequency band enables precise decoding of visual information during both perception and sustained storage in working memory. Extant work, however, has focused exclusively on the representation of static visual images. Here we used EEG recordings to examine whether alpha-band activity supports the dynamic transformation of representations in spatial working memory using an imagery task that required the active shifting of a stored position to a new position. In line with recent findings, a common format of alpha-band activity precisely tracked both the initial position stored in working memory as well as the transformed position, with the latter emerging approximately 800-1200 ms following an auditory cue to "rotate" to a new position. Moreover, the time course of this transformation of alpha activity predicted between-subject differences in manual reaction time to indicate the new position (Experiment 1), as well as within-subject variations in saccade latency in a speeded version of the task (Experiment 2). Finally, cross-training analyses revealed robust generalization of alpha-band reconstruction of working memory contents before and after mental transformation. These findings demonstrate that alpha activity tracks dynamic transformations of representations in spatial working memory, and that the format of this activity is preserved across the initial and transformed memory representations. These findings highlight a new approach for measuring voluntary shifts in online memory representations and show common representational formats during dynamic mental imagery and the maintenance of static representations in working memory.

neuroscience↗

bioRxiv2021

Pupillometry signatures of sustained attention and working memory

There exists an intricate relationship between attention and working memory. Recent work has further established that attention and working memory fluctuate synchronously, by tightly interleaving sustained attention and working memory tasks. This work has raised many open questions about physiological signatures underlying these behavioral fluctuations. Across two experiments, we explore pupil dynamics using real-time triggering in conjunction with an interleaved sustained attention and working memory task. In Experiment 1, we use behavioral real-time triggering and replicate recent findings from our lab (deBettencourt et al., 2019) that sustained attention fluctuates concurrently with the number of items maintained in working memory. Furthermore, highly attentive moments, detected via behavior, also exhibited larger pupil sizes. In Experiment 2, we develop a novel real-time pupil triggering technique to track pupil size fluctuations in real time and trigger working memory probes. We reveal that this pupil triggering procedure elicits differences in sustained attention, as indexed by response time. These experiments reflect methodological advances in real-time triggering and further characterize an important biomarker of sustained attention.

neuroscience↗

bioRxiv2020

Sustained attention and spatial attention distinctly influence long-term memory encoding

Our attention is critically important for what we remember. Prior measures of the relationship between attention and memory, however, have largely treated "attention" as a monolith. Here, across three experiments, we provide evidence for two dissociable aspects of attention that influence encoding into long-term memory. Using spatial cues together with a sensitive continuous report procedure, we find that long-term memory response error is affected by both trial-by-trial fluctuations of sustained attention and prioritization via covert spatial attention. Furthermore, using multivariate analyses of EEG, we track both sustained attention and spatial attention prior to stimulus onset. Intriguingly, even during moments of low sustained attention, there is no decline in the representation of the spatially attended location, showing that these two aspects of attention have robust but independent effects on long term memory encoding. Finally, sustained and spatial attention predicted distinct variance in long-term memory performance across individuals. That is, the relationship between attention and long-term memory suggests a composite model, wherein distinct attentional subcomponents influence encoding into long-term memory. These results point towards a taxonomy of the distinct attentional processes that constrain our memories.

neuroscience↗

bioRxiv2020

Controlling the flow of interruption in working memory

Visual working memory (WM) must maintain relevant information, despite the constant influx of both relevant and irrelevant information. Attentional control mechanisms help determine which of this new information gets access to our capacity-limited WM system. Previous work has treated attentional control as a monolithic process-either distractors capture attention or they are suppressed. Here, we provide evidence that attentional capture may instead be broken down into at least two distinct sub-component processes: 1) spatial capture, which refers to when spatial attention shifts towards the location of irrelevant stimuli, and 2) item-based capture, which refers to when item-based WM representations of irrelevant stimuli are formed. To dissociate these two sub-component processes of attentional capture, we utilized a series of EEG components that track WM maintenance (contralateral delay activity), suppression (distractor positivity), item individuation (N2pc), and spatial attention (lateralized alpha power). We show that relevant interrupters trigger both spatial and item-based capture, which means that they undermine WM maintenance more. Irrelevant interrupters, however, only trigger spatial capture from which ongoing WM representations can recover more easily. This fractionation of attentional capture into distinct sub-component processes provides a framework by which the fate of ongoing WM processes after interruption can be explained.

neuroscience↗

bioRxiv2020

Predicting cognitive abilities across individuals using sparse EEG connectivity

Human brains share a broadly similar functional organization with consequential individual variation. This duality in brain function has primarily been observed when using techniques that consider the spatial organization of the brain, such as MRI. Here, we ask whether these common and unique signals of cognition are also present in temporally sensitive, but spatially insensitive, neural signals. To address this question, we compiled EEG data from individuals performing multiple working memory tasks at two different data-collection sites (ns = 171 and 165). Results revealed that EEG connectivity patterns were stable within individuals and unique across individuals. Furthermore, models based on these connectivity patterns generalized across datasets to predict participants working memory capacity and general fluid intelligence. Thus, EEG connectivity provides a signature of working memory and fluid intelligence in humans and a new framework for characterizing individual differences in cognitive abilities.

neuroscience↗

bioRxiv2020

Multivariate analysis reveals a generalizable human electrophysiological signature of working memory load

Working memory (WM) is an online memory system that is critical for holding information in a rapidly accessible state during ongoing cognitive processing. Thus, there is strong value in methods that provide a temporally-resolved index of WM load. While univariate EEG signals have been identified that vary with WM load, recent advances in multivariate analytic approaches suggest that there may be rich sources of information that do not generate reliable univariate signatures. Here, using data from 4 published studies (n = 286 and >250,000 trials), we demonstrate that multivariate analysis of EEG voltage topography provides a sensitive index of the number of items stored in WM that generalizes to novel human observers. Moreover, multivariate load detection ("mvLoad") can provide robust information at the single-trial level, exceeding the sensitivity of extant univariate approaches. We show that this method tracks WM load in a manner that is (1) independent of the spatial position of the memoranda, (2) precise enough to differentiate item-by-item increments in the number of stored items, (3) generalizable across distinct tasks and stimulus displays and (4) correlated with individual differences in WM behavior. Thus, this approach provides a powerful complement to univariate analytic approaches, enabling temporally-resolved tracking of online memory storage in humans.

neuroscience↗

bioRxiv2019

Δ9-Tetrahydrocannabinol (THC) impairs visual working memory performance

With the increasing prevalence of legal cannabis use and availability, there is an urgent need to identify cognitive impairments related to its use. It is widely believed that cannabis, or its main psychoactive component {Delta}9-tetrahydrocannabinol (THC), impairs working memory, i.e., the ability to temporarily hold information in mind. However, our review of the literature yielded surprisingly little empirical support for an effect of THC or cannabis on working memory. We thus conducted a study with 3 main goals: (1) quantify the effect of THC on visual working memory in a well-powered sample (2) test the potential role of cognitive effects (mind wandering and metacognition) in disrupting working memory, and (3) demonstrate how insufficient sample size and task duration reduce the likelihood of detecting a drug effect. We conducted two double-blind, randomized crossover experiments in which healthy adults (N=23, 23) performed a reliable and validated visual working memory task (the "Discrete Whole-Report task", 90 trials) after administration of THC (7.5 and/or 15 mg oral) or placebo. We also assessed self-reported mind wandering (Exp 1) and metacognitive accuracy about ongoing task performance (Exp 2). THC impaired working memory performance (d = .65), increased mind wandering (Exp 1), and decreased metacognitive accuracy about task performance (Exp 2). Thus, our findings indicate that THC does impair visual working memory, and that this impairment may be related to both increased mind-wandering and decreased monitoring of task performance. Finally, we used a down-sampling procedure to illustrate the effects of task length and sample size on power to detect the acute effect of THC on working memory.

pharmacology and toxicology↗